Difference between revisions of "Music culture as a social network (Fall 2011)"

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(Sources of online network data)
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* Internet content
* Internet content
** Bing (for word co-occurrence matrices - note that Bing provides the near:N search modifier; placed between two phrases it requires that they be separated by no more than N words)
** Bing (for word co-occurrence matrices - note that Bing provides the near:N search modifier; placed between two phrases it requires that they be separated by no more than N words)
** link: keywords (to tell Google to find pages that link to an artist page, thus establishing its ego net)
* Internet searching
* Internet searching
** http://www.google.com/insights/search/# (enables matrix of search vs. locale)
** http://www.google.com/insights/search/# (enables matrix of search vs. locale)

Revision as of 16:40, 30 June 2011

short link: http://bit.ly/mcsn

MUSIC 466/566 LEC A1 T R 11:00AM - 12:20PM
HC (Humanities Centre) room 4-78 (available for undergraduate or graduate credit)

Note: the following course outline is not yet finalized!


SNA segment.png

These days, social networks seem to be everywhere, especially with the advent of "social networking" as a catchphrase, new web-based social networking services such as Facebook, and popularization of social network concepts such as six degrees of separation, and small-world networks[1]. But the idea of using graph theory to understand social groups and culture goes back nearly a century, while social networks themselves are intrinsic to being human. [2][3]

Ethnomusicology is typically defined as the study of music in society or the study of music as culture...if social network analysis (SNA) is an important approach towards understanding society and culture, then it follows that SNA should also provide an insightful means of thinking in ethnomusicology, and a productive tool for ethnomusicological research.

Yet few ethnomusicologists have explored SNA's possibilities, perhaps because SNA appears inaccessible, filed under "mathematical sociology," while music scholars have tended to prefer the more qualitative, critical, and interpretive approaches of the human sciences. SNA also presents some challenging methodological difficulties for fieldworkers - mapping social networks is not always easy, practically and ethically. Yet SNA's origins lies in social anthropology, a field with longstanding connections to ethnomusicology. Methodologically SNA is more feasible today, with the emergence of online virtual communities, defined by social networking websites, and other electronic communications. And the basic mathematics required to understand SNA is quite elementary.

This seminar-workshop attempts to bridge the gap between traditional humanistic scholarship and SNA by providing a gentle introduction to methods, theories, and issues in social network analysis,with applications to ethnomusicology. You won’t merely read about social network analysis, you’ll actually do it!

Ethnomusicological applications of SNA include understanding the ways musicians and audiences interact in performance; network aspects of celebrity formation; exploring communities of musical taste; understanding the circulation of online music; analyzing the role of music in the structure of online social networks (Facebook, Twitter, Myspace...and others specifically devoted to music); investigating networks of musical friendship, prestige, and respect; examining linkages between music sites on the Internet; considering networks generated by musical collaborations (e.g. composer-lyricist relations); the overlap of friendship and musical collaboration network; small world networks in the arts (c.f. Degrees of Kevin Bacon[4]); affiliation networks of numerous types; and many other topics.

Course requirements

  • Weekly...
    • lectures and discussions
    • readings
    • computer “lab work” accompanying readings, using free SNA software tools (mainly Pajek) allowing you to develop an intuitive grasp of network concepts
    • problem sets, to learn and reinforce concepts from your reading (typically assigned on Thursday, due on Tuesday)
  • Three short (20 minute) quizzes (Sep 22, Oct 13, Nov 3), to motivate and assess learning
  • SNA research project of your choosing, including planning, data gathering, analysis, interpretation, class presentation (20 min), and writeup as a final paper
    • First project proposal draft due Oct 27 (resubmitted until acceptable)
    • Class presentations (Nov 29

There is no final exam.

If possible, bring your laptop to class, so we can use the software together.


The evaluation of each requirement is on a scale from 0-4 points. These scores are combined according to the percentages indicated in order to produce a final numeric grade. This grade is rounded to the nearest numeric value in the table below, in order to determine the final letter grade. In exceptional cases the grade A+ may also be assigned. Expectations for the 500 level are higher than for the 400 level. Unexcused late assignments will be downgraded one quarter point per day late. The only valid excuse is a documented medical or family emergency. Please take care to plan ahead, bearing in mind due dates for your other courses.

  • Attendance and class participation: 15%
  • Problem sets: 20% total (for about 10 assignments)
  • Quizzes: 6.6666% each (20% total)
  • Project proposal: 5%
  • Research class presentation: 10%
  • Research paper: 30%

A A- B+ B B- C+ C C- D+ D F
4.0 3.7 3.3 3.0 2.7 2.3 2.0 1.7 1.3 1.0 0.0

Required texts

Robert A. Hanneman and Mark Riddle. Introduction to social network methods (also available as a pdf. Free.) Works well with Netdraw (which works only on PCs, or Macs in Windows compatibility mode).

Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj, Exploratory Social Network Analysis with Pajek, illustrated edition. (Cambridge University Press, 2005). (Available in the SUB bookstore.) Works well with Pajek (which was created for PCs but also runs fine on Macs).

Optional texts

John P Scott, Social Network Analysis: A Handbook, 2nd ed. (Sage Publications Ltd, 2000). (Available in the SUB bookstore.) (succinct summary)

Linton C. Freeman, The Development of Social Network Analysis: A Study in the Sociology of Science (Empirical Press, 2004). (for those interested in SNA"s intellectual history)

Wasserman, Stanley and Faust, Katherine. Social network analysis methods and applications. Cambridge, New York: Cambridge University Press; 1994. (for those who want a more complete and rigorous treatment)

Popular treatments

Albert-Laszlo Barabasi, Linked: How Everything Is Connected to Everything Else and What It Means (Plume, 2003).

Duncan J. Watts, Six Degrees: The Science of a Connected Age (W. W. Norton & Company, 2004).

Malcolm Gladwell, The Tipping Point: How Little Things Can Make a Big Difference (Back Bay Books, 2002).

Nicholas A. Christakis and James H. Fowler, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (New York: Little, Brown and Company). (A popular science treatment.)

Software (all free!)

Pajek for Windows or Mac (required - accompanies textbook)

NodeXL for Excel (Windows only)







International Network for Social Network Analysis (professional society - with lots of links, naturally!)

Wiki for SNA

Social Network Analysis Instructional Web Site

David Easley and Jon Kleinberg's Interdisciplinary networks course at Cornell University (cross-listed in computer science, economics, sociology, information science)

Kinds of music networks

  • affiliation networks
    • musicians/groups: co-membership
    • fan clubs and groups
    • musical taste networks (people who like this music also like this...)
  • relation between friendship networks and musical attributes (taste, performance, consumption, breadth)
  • structure of musician communication networks
  • product networks (co-purchase, e.g. Amazon)
  • musical flow/awareness
  • communication networks in performance
  • transmission: teaching and learning networks
  • networks of musical collaboration (e.g. composer/lyricist networks, co-member networks)
  • small world networks
  • musical prestige and authority
  • scale-free networks & celebrity
  • egonets and music attributes (performance, consumption, taste, breadth)
  • citation and co-author networks
  • webpage word co-occurrence (e.g. musical genres)

Sources of online network data

Possible short learning projects

  • Shared FB friends among class members
  • Musical taste implications
  • Observation of conversational interactions
  • Plot networks in films about musicians
  • Ego-alter networks
  • Friendship networks
  • Musical affiliations
  • Flow: how you learn about music from friends...
  • Literary connections through song lyrics
  • Composer-lyricist networks

Mathematica demos

Instructive, and fun to play with (btw, Mathematica is wonderful...but pricey)















Social nets